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Python Code Samples

Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.

83 matches
ML engineering pipelines medium

How to Stage ML Model Workflows with Python Classes

Defines a Stage class to model ML pipeline stages with variants and mocks, printing grammar for Model, Staging, and Production stages.

ml-pipelines stages model-deployment
Python
class Stage:
    def __init__(self, name):
        self.name = name
        self.mocks = []
        self.variants = []

    def add_mock(self, mock_name):
        self.mocks.append(mock_name)

    def add_variant(self, variant_name, productions=()):
        self.variants.append((variant_name, list(productions)))

    …
12 0 Open
ML engineering pipelines medium

Mock a Flyte ML workflow in Python

Build a lightweight mock of a Flyte ML pipeline with dataclasses and a simple execution loop that passes outputs between tasks.

flyte ml-pipeline dataclass
Python
from dataclasses import dataclass, field
from typing import List, Dict, Optional
import time


@dataclass
class FlyteTask:
    name: str
    inputs: Dict = field(default_factory=dict)
    outputs: Dict = field(default_factory=dict)

    def run(self) -> Dict:
        time.sleep(0.1)  # simulate work
        return sel…
16 0 Open
Database scaling & optimization medium

Cross Shard Query Scatter Gather Mock in Python

Simulate a distributed database cross-shard query using a scatter-gather pattern with a mock Python implementation.

scatter-gather sharding distributed-systems
Python
from dataclasses import dataclass
from typing import List, Dict


@dataclass
class NodeResponse:
    node_id: int
    data: Dict[str, float]


def mock_query_shard(shard_id: int, shard_data: Dict[str, float], query: str) -> NodeResponse:
    """Simulate querying a single shard, returning matches whose value > 50."""
 …
13 0 Open
Database scaling & optimization easy

How to Replicate Data Across All Shards in Python

Mocks a global table that replicates a key-value pair to every shard, ensuring reads return the same value from any shard.

sharding replication distributed systems
Python
from dataclasses import dataclass
from typing import Dict, List


@dataclass
class Shard:
    id: str
    data: Dict[str, int]


class GlobalTable:
    def __init__(self, shards: List[Shard]):
        self._shards = {s.id: s for s in shards}

    def set_value(self, key: str, value: int) -> None:
        """Replicate …
14 0 Open
Production deployment patterns medium

How to Build a GitOps Argo CD Sync Mock in Python

Simulate Argo CD-style GitOps deployment sync with Python dataclasses, random success rates, and force-sync retry logic.

gitops argo-cd deployment
Python
import random
import time
from dataclasses import dataclass, field
from typing import List, Dict


@dataclass
class Application:
    name: str
    source_repo: str
    target_revision: str
    synced: bool = False
    health_status: str = "Healthy"
    history: List[Dict] = field(default_factory=list)

    def sync(se…
13 0 Open
Production deployment patterns easy

How to Mock Multi-Stage Docker Builds in Python

Simulate a multi-stage Docker build in pure Python using classes and temp directories to understand how build stages copy artifacts into a final image.

docker multi-stage simulation
Python
# Simulate multi-stage Docker build with pure Python
from pathlib import Path
import tempfile
import shutil

class BuildContext:
    """Mimics a Docker build context with stages."""
    
    def __init__(self, name):
        self.name = name
        self.files = {}
    
    def add_file(self, dest, content):
        s…
14 0 Open
Production deployment patterns easy

How to Mock a CI Pipeline with Build, Test, and Deploy Stages in Python

Simulate a three-stage CI pipeline (build, test, deploy) in Python with random pass/fail logic, early exit on failure, and measured stage durations.

ci-cd simulation dataclasses
Python
import time
import random
from dataclasses import dataclass


@dataclass
class StageResult:
    name: str
    status: str
    duration: float


def run_stage(name: str, success_chance: float = 0.9) -> StageResult:
    """Simulate a pipeline stage with random success/failure."""
    start = time.time()
    time.sleep(r…
14 0 Open
Production deployment patterns easy

How to Mock a Dockerfile Multi-Stage Build in Python

Simulate a Dockerfile multi-stage build process in Python using dataclasses to validate stage ordering and file availability before you write the real Dockerfile.

dockerfile multi-stage simulation
Python
from dataclasses import dataclass
from pathlib import Path


@dataclass
class BuildStage:
    name: str
    base_image: str
    files: list[str]
    commands: list[str]


def run_build(stage: BuildStage, context_dir: Path):
    print(f"=== Stage: {stage.name} (base: {stage.base_image}) ===")
    for file in stage.file…
14 0 Open
Production deployment patterns easy

How to Mock a Feature Flag Rollout Percentage in Python

Simulate a percentage-based feature flag rollout by hashing a user ID to deterministically enable features for a subset of users.

feature-flags rollout deterministic
Python
import random
from dataclasses import dataclass


@dataclass
class FeatureFlag:
    name: str
    rollout_percentage: int


def is_feature_enabled(feature_flag: FeatureFlag, user_id: str) -> bool:
    hashed_id = hash(user_id) % 100
    return hashed_id < feature_flag.rollout_percentage


if __name__ == "__main__":
  …
11 0 Open
Production deployment patterns easy

How to Mock a GitHub Actions Workflow in Python

Build a dataclass-based model of a GitHub Actions workflow and simulate its execution to validate steps and outputs before deployment.

github-actions dataclasses mock
Python
import json
from dataclasses import dataclass, asdict
from typing import List, Dict, Any


@dataclass
class Step:
    name: str
    run: str


@dataclass
class Job:
    name: str
    steps: List[Step]
    runs_on: str = "ubuntu-latest"


@dataclass
class Workflow:
    name: str
    jobs: List[Job]

    def to_github_a…
13 0 Open
Production deployment patterns easy

How to Replace Fields in an Immutable Dataclass in Python

Create a new copy of a frozen dataclass with selected fields changed, leaving the original unchanged.

dataclasses immutable configuration
Python
from dataclasses import dataclass, replace


@dataclass(frozen=True)
class ServerConfig:
    name: str
    cpu: int = 2
    ram: int = 4096
    tags: tuple = ()


original = ServerConfig("web-01", cpu=4, tags=("env:prod",))
updated = replace(original, ram=8192, tags=("env:prod", "region:us-east"))

print("Original:", …
15 0 Open

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